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Daniel Buncic

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Daniel Buncic & Adrian Pagan, 2022. "Discovering Stars: Problems in Recovering Latent Variables from Models," CAMA Working Papers 2022-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Buncic, Daniel, 2024. "Econometric issues in the estimation of the natural rate of interest," Economic Modelling, Elsevier, vol. 132(C).
    2. Ye Lu & Adrian Pagan, 2023. "To Boost or Not to Boost? That is the Question," Working Papers 2023-05, University of Sydney, School of Economics.

  2. Daniel Buncic, 2021. "On a Standard Method for Measuring the Natural Rate of Interest," Papers 2103.16452, arXiv.org, revised Apr 2022.

    Cited by:

    1. Daniel Buncic & Adrian Pagan & Tim Robinson, 2023. "Recovering Stars in Macroeconomics," CAMA Working Papers 2023-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Buncic, Daniel, 2024. "Econometric issues in the estimation of the natural rate of interest," Economic Modelling, Elsevier, vol. 132(C).

  3. Daniel Buncic, 2020. "Econometric issues with Laubach and Williams' estimates of the natural rate of interest," Papers 2002.11583, arXiv.org, revised Aug 2020.

    Cited by:

    1. Darracq Pariès, Matthieu & Notarpietro, Alessandro & Kilponen, Juha & Papadopoulou, Niki & Zimic, Srečko & Aldama, Pierre & Langenus, Geert & Alvarez, Luis Julian & Lemoine, Matthieu & Angelini, Elena, 2021. "Review of macroeconomic modelling in the Eurosystem: current practices and scope for improvement," Occasional Paper Series 267, European Central Bank.
    2. Jair Ojeda-Joya, 2022. "A Counterfactual Analysis of the Effects of Climate Change on the Natural Interest Rate," IHEID Working Papers 10-2022, Economics Section, The Graduate Institute of International Studies.
    3. Dilian Vassilev, 2021. "A Model of Natural Interest Rate: The Case of Bulgaria," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 7, pages 46-72.
    4. Daniel Buncic, 2021. "On a Standard Method for Measuring the Natural Rate of Interest," Papers 2103.16452, arXiv.org, revised Apr 2022.

  4. Buncic, Daniel, 2017. "Identification and Estimation issues in Exponential Smooth Transition Autoregressive Models," Working Paper Series 344, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Esmaeil Ebadi & Yousef Abdul Razaq, 2024. "Reinvestigating the Oil Dependency of the GCC Countries’ Stock Market: A Regime-Switching Cointegration Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 14(3), pages 387-406, May.
    2. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-19, Department of Economics and Business Economics, Aarhus University.
    3. Selin Güney & Andrés Riquelme & Barry Goodwin, 2023. "An Analysis of the Pass-Through of Exchange Rates in Forest Product Markets," Agriculture, MDPI, vol. 13(3), pages 1-16, February.
    4. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2018. "The Shifting Seasonal Mean Autoregressive Model and Seasonality in the Central England Monthly Temperature Series, 1772-2016," CREATES Research Papers 2018-15, Department of Economics and Business Economics, Aarhus University.
    5. Dimitris Christopoulos & Peter McAdam & Elias Tzavalis, 2023. "Exploring Okun's law asymmetry: An endogenous threshold logistic smooth transition regression approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(1), pages 123-158, February.
    6. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
    7. Elias, Nikolaos & Smyrnakis, Dimitris & Tzavalis, Elias, 2024. "The forward premium anomaly and the currency carry trade hypothesis," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 203-218.
    8. Anoop Chaturvedi & Shivam Jaiswal, 2020. "Bayesian Estimation and Unit Root Test for Logistic Smooth Transition Autoregressive Process," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(4), pages 733-745, December.

  5. Buncic, Daniel & Gisler, Katja I. M., 2015. "Global Equity Market Volatility Spillovers: A Broader Role for the United States," Economics Working Paper Series 1508, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Li, Yan & Liang, Chao & Ma, Feng & Wang, Jiqian, 2020. "The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 36(C).
    2. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2018. "Textual Sentiment, Option Characteristics, and Stock Return Predictability," IRTG 1792 Discussion Papers 2018-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    4. Ballinari, Daniele & Audrino, Francesco & Sigrist, Fabio, 2022. "When does attention matter? The effect of investor attention on stock market volatility around news releases," International Review of Financial Analysis, Elsevier, vol. 82(C).
    5. Wang, Jiqian & Lu, Xinjie & He, Feng & Ma, Feng, 2020. "Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    6. Ding, Hui & Huang, Yisu & Wang, Jiqian, 2023. "Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    7. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2022. "Media-expressed tone, option characteristics, and stock return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    8. Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
    9. Chao Liang & Yaojie Zhang & Xiafei Li & Feng Ma, 2022. "Which predictor is more predictive for Bitcoin volatility? And why?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1947-1961, April.
    10. Dimos Kambouroudis & David McMillan & Katerina Tsakou, 2019. "Forecasting Realized Volatility: The role of implied volatility, leverage effect, overnight returns and volatility of realized volatility," Working Papers 2019-03, Swansea University, School of Management.
    11. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    12. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    13. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    14. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2021. "Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1618-1639, October.
    15. Francesco Audrino & Jonathan Chassot, 2024. "HARd to Beat: The Overlooked Impact of Rolling Windows in the Era of Machine Learning," Papers 2406.08041, arXiv.org.
    16. Wu, Lan & Xu, Weiju & Huang, Dengshi & Li, Pan, 2022. "Does the volatility spillover effect matter in oil price volatility predictability? Evidence from high-frequency data," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 299-306.
    17. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    18. Delis, Panagiotis & Degiannakis, Stavros & Giannopoulos, Kostantinos, 2021. "What should be taken into consideration when forecasting oil implied volatility index?," MPRA Paper 110831, University Library of Munich, Germany.
    19. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    20. Christian Manicaro, 2022. "The link between regional CDS spreads and equity returns: a multivariate GARCH approach," SN Business & Economics, Springer, vol. 2(2), pages 1-15, February.
    21. Chao Zhang & Xingyue Pu & Mihai Cucuringu & Xiaowen Dong, 2023. "Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects," Papers 2308.01419, arXiv.org.
    22. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
    23. Chao Liang & Yan Li & Feng Ma & Yaojie Zhang, 2022. "Forecasting international equity market volatility: A new approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1433-1457, November.
    24. Bazán-Palomino, Walter, 2023. "The increased interest in Bitcoin and the immediate and long-term impact of Bitcoin volatility on global stock markets," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1080-1095.
    25. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    26. Kang, Yong Joo & Park, Dojoon & Eom, Young Ho, 2024. "Global contagion of US COVID-19 panic news," Emerging Markets Review, Elsevier, vol. 59(C).
    27. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
    28. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Sivaprasad, Sheeja, 2021. "The impact of Covid-19 on G7 stock markets volatility: Evidence from a ST-HAR model," International Review of Financial Analysis, Elsevier, vol. 74(C).
    29. Papież, Monika & Rubaszek, Michał & Szafranek, Karol & Śmiech, Sławomir, 2022. "Are European natural gas markets connected? A time-varying spillovers analysis," Resources Policy, Elsevier, vol. 79(C).
    30. Nguyen, Linh Hoang & Lambe, Brendan John, 2021. "International tail risk connectedness: Network and determinants," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    31. Chao Liang & Yu Wei & Yaojie Zhang, 2020. "Is implied volatility more informative for forecasting realized volatility: An international perspective," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1253-1276, December.
    32. Chao Liang & Yi Zhang & Yaojie Zhang, 2022. "Forecasting the volatility of the German stock market: New evidence," Applied Economics, Taylor & Francis Journals, vol. 54(9), pages 1055-1070, February.
    33. Tong Fang & Deyu Miao & Zhi Su & Libo Yin, 2023. "Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 872-904, July.
    34. Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility," Resources Policy, Elsevier, vol. 79(C).
    35. Buncic, Daniel & Gisler, Katja I.M., 2017. "The role of jumps and leverage in forecasting volatility in international equity markets," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 1-19.
    36. Panagiotis Delis & Stavros Degiannakis & George Filis, 2022. "What matters when developing oil price volatility forecasting frameworks?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 361-382, March.
    37. Chao Liang & Yu Wei & Likun Lei & Feng Ma, 2022. "Global equity market volatility forecasting: New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 594-609, January.
    38. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    39. Ana Monteiro & Nuno Silva & Helder Sebastião, 2023. "Industry return lead-lag relationships between the US and other major countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-48, December.
    40. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
    41. Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
    42. Dlugosch, Dennis & Wang, Mei, 2022. "Ambiguity, ambiguity aversion and foreign bias: New evidence from international panel data," Journal of Banking & Finance, Elsevier, vol. 140(C).
    43. Wang, Jiqian & Ma, Feng & Wang, Tianyang & Wu, Lan, 2023. "International stock volatility predictability: New evidence from uncertainties," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    44. Chen, Zhonglu & Liang, Chao & Umar, Muhammad, 2021. "Is investor sentiment stronger than VIX and uncertainty indices in predicting energy volatility?," Resources Policy, Elsevier, vol. 74(C).
    45. Maghyereh, Aktham & Awartani, Basel & Abdoh, Hussein, 2022. "Asymmetric risk transfer in global equity markets: An extended sample that includes the COVID pandemic period," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).

  6. Buncic, Daniel & Tischhauser, Martin, 2015. "Macroeconomic Factors and Equity Premium Predictability," Economics Working Paper Series 1522, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2019. "Forecasting stock returns with cycle-decomposed predictors," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 250-261.
    2. Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
    3. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    4. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    5. Oguzhan Cepni & Rangan Gupta & I. Ethem Guney & M. Hasan Yilmaz, 2019. "Forecasting Local Currency Bond Risk Premia of Emerging Markets: The Role of Cross-Country Macro-Financial Linkages," Working Papers 201957, University of Pretoria, Department of Economics.
    6. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).

  7. Buncic, Daniel & Piras, Gion Donat, 2014. "Heterogeneous Agents, the Financial Crisis and Exchange Rate Predictability," Economics Working Paper Series 1436, University of St. Gallen, School of Economics and Political Science, revised Oct 2015.

    Cited by:

    1. Yamani, Ehab, 2019. "Diversification role of currency momentum for carry trade: Evidence from financial crises," Journal of Multinational Financial Management, Elsevier, vol. 49(C), pages 1-19.
    2. Buncic, Daniel & Lentner, Philipp, 2016. "The term structure of interest rates in an estimated New Keynesian policy model," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 126-150.
    3. Li, Xiao-Ping & Zhou, Chun-Yang & Tong, Bin, 2019. "Carry trades, agent heterogeneity and the exchange rate," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 343-358.
    4. Daniel Buncic, 2016. "Superforecasting: The Art and Science of Prediction. By Philip Tetlock and Dan Gardner," Risks, MDPI, vol. 4(3), pages 1-5, July.
    5. Gardini, Laura & Radi, Davide & Schmitt, Noemi & Sushko, Iryna & Westerhoff, Frank, 2022. "Currency manipulation and currency wars: Analyzing the dynamics of competitive central bank interventions," Journal of Economic Dynamics and Control, Elsevier, vol. 145(C).
    6. Polyzos, Stathis & Samitas, Aristeidis & Kampouris, Ilias, 2021. "Economic stimulus through bank regulation: Government responses to the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    7. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    8. Antonios K. Alexandridis & Ekaterini Panopoulou & Ioannis Souropanis, 2024. "Forecasting exchange rates: An iterated combination constrained predictor approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 983-1017, July.
    9. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    10. Yamani, Ehab, 2021. "Foreign exchange market efficiency and the global financial crisis: Fundamental versus technical information," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 74-89.
    11. Yamani, Ehab, 2021. "Can technical trading beat the foreign exchange market in times of crisis?," Global Finance Journal, Elsevier, vol. 48(C).
    12. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    13. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    14. Zhang, Qian & Li, Zeguang, 2021. "Time-varying risk attitude and the foreign exchange market behavior," Research in International Business and Finance, Elsevier, vol. 57(C).
    15. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    16. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    17. Qian Zhang & Kuo-Jui Wu & Ming-Lang Tseng, 2019. "Exploring Carry Trade and Exchange Rate toward Sustainable Financial Resources: An application of the Artificial Intelligence UKF Method," Sustainability, MDPI, vol. 11(12), pages 1-26, June.
    18. Piotr Dybka, 2020. "One model or many? Exchange rates determinants and their predictive capabilities," KAE Working Papers 2020-053, Warsaw School of Economics, Collegium of Economic Analysis.
    19. Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.

  8. Buncic, Daniel & Moretto, Carlo, 2014. "Forecasting Copper Prices with Dynamic Averaging and Selection Models," Economics Working Paper Series 1430, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Buncic, Daniel & Lentner, Philipp, 2016. "The term structure of interest rates in an estimated New Keynesian policy model," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 126-150.
    2. Jan Prüser, 2019. "Adaptive learning from model space," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(1), pages 29-38, January.
    3. Krzysztof Drachal, 2018. "Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework," Energies, MDPI, vol. 11(5), pages 1-24, May.
    4. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    5. Zhang, Hong & Nguyen, Hoang & Bui, Xuan-Nam & Pradhan, Biswajeet & Mai, Ngoc-Luan & Vu, Diep-Anh, 2021. "Proposing two novel hybrid intelligence models for forecasting copper price based on extreme learning machine and meta-heuristic algorithms," Resources Policy, Elsevier, vol. 73(C).
    6. Su, Chi Wei & Song, Xin Yue & Qin, Meng & Lobonţ, Oana-Ramona, 2024. "Is copper a safe haven for oil?," Resources Policy, Elsevier, vol. 91(C).
    7. Fernandez, Viviana, 2020. "The predictive power of convenience yields," Resources Policy, Elsevier, vol. 65(C).
    8. Drachal, Krzysztof, 2019. "Forecasting prices of selected metals with Bayesian data-rich models," Resources Policy, Elsevier, vol. 64(C).
    9. Alameer, Zakaria & Elaziz, Mohamed Abd & Ewees, Ahmed A. & Ye, Haiwang & Jianhua, Zhang, 2019. "Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm," Resources Policy, Elsevier, vol. 61(C), pages 250-260.
    10. Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2015. "Behavioral influences in non-ferrous metals prices," Resources Policy, Elsevier, vol. 45(C), pages 9-22.
    11. Zian Wang & Xinshu Li, 2024. "On the macroeconomic fundamentals of long-term volatilities and dynamic correlations in COMEX copper futures," Papers 2409.08355, arXiv.org.
    12. Liu, Kailei & Cheng, Jinhua & Yi, Jiahui, 2022. "Copper price forecasted by hybrid neural network with Bayesian Optimization and wavelet transform," Resources Policy, Elsevier, vol. 75(C).
    13. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    14. Su, Chi-Wei & Wang, Xiao-Qing & Zhu, Haotian & Tao, Ran & Moldovan, Nicoleta-Claudia & Lobonţ, Oana-Ramona, 2020. "Testing for multiple bubbles in the copper price: Periodically collapsing behavior," Resources Policy, Elsevier, vol. 65(C).
    15. Hardy, Nicolás & Ferreira, Tiago & Quinteros, Maria J. & Magner, Nicolás S., 2023. "“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone," Resources Policy, Elsevier, vol. 86(PA).
    16. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    17. Pincheira, Pablo & Hardy, Nicolas, 2018. "The predictive relationship between exchange rate expectations and base metal prices," MPRA Paper 89423, University Library of Munich, Germany.
    18. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    19. Pincheira Brown, Pablo & Hardy, Nicolás, 2019. "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, vol. 62(C), pages 256-281.
    20. Liu, Chang & Hu, Zhenhua & Li, Yan & Liu, Shaojun, 2017. "Forecasting copper prices by decision tree learning," Resources Policy, Elsevier, vol. 52(C), pages 427-434.
    21. Boriss Siliverstovs, 2015. "Dissecting Models' Forecasting Performance," KOF Working papers 15-397, KOF Swiss Economic Institute, ETH Zurich.
    22. Wang, Chao & Zhang, Xinyi & Wang, Minggang & Lim, Ming K. & Ghadimi, Pezhman, 2019. "Predictive analytics of the copper spot price by utilizing complex network and artificial neural network techniques," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    23. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2021. "Economic drivers of commodity volatility: The case of copper," Resources Policy, Elsevier, vol. 73(C).
    24. Yifei Zhao & Jianhong Chen & Hideki Shimada & Takashi Sasaoka, 2023. "Non-Ferrous Metal Price Point and Interval Prediction Based on Variational Mode Decomposition and Optimized LSTM Network," Mathematics, MDPI, vol. 11(12), pages 1-16, June.
    25. Harald Ulrik Sverdrup & Anna Hulda Olafsdottir, 2020. "Conceptualization and parameterization of the market price mechanism in the WORLD6 model for metals, materials, and fossil fuels," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 33(3), pages 285-310, October.
    26. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    27. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2020. "A random walk through the trees: Forecasting copper prices using decision learning methods," Resources Policy, Elsevier, vol. 69(C).
    28. Krzysztof Drachal, 2019. "Analysis of Agricultural Commodities Prices with New Bayesian Model Combination Schemes," Sustainability, MDPI, vol. 11(19), pages 1-23, September.
    29. Gemici, Eray & Gök, Remzi & Bouri, Elie, 2023. "Predictability of risk appetite in Turkey: Local versus global factors," Emerging Markets Review, Elsevier, vol. 55(C).
    30. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    31. Ewees, Ahmed A. & Elaziz, Mohamed Abd & Alameer, Zakaria & Ye, Haiwang & Jianhua, Zhang, 2020. "Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility," Resources Policy, Elsevier, vol. 65(C).
    32. Schischke, A. & Papenfuß, P. & Brem, M. & Kurz, P. & Rathgeber, A.W., 2023. "Sustainable energy transition and its demand for scarce resources: Insights into the German Energiewende through a new risk assessment framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    33. Mastroeni, Loretta & Vellucci, Pierluigi & Naldi, Maurizio, 2018. "Co-existence of stochastic and chaotic behaviour in the copper price time series," Resources Policy, Elsevier, vol. 58(C), pages 295-302.
    34. Becerra, Miguel & Jerez, Alejandro & Garcés, Hugo O. & Demarco, Rodrigo, 2022. "Copper price: A brief analysis of China’s impact over its short-term forecasting," Resources Policy, Elsevier, vol. 75(C).
    35. Hammami, Yacine & Zhu, Jie, 2020. "Understanding time-varying short-horizon predictability✰," Finance Research Letters, Elsevier, vol. 32(C).
    36. Drachal, Krzysztof, 2018. "Comparison between Bayesian and information-theoretic model averaging: Fossil fuels prices example," Energy Economics, Elsevier, vol. 74(C), pages 208-251.
    37. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    38. Piotr Dybka, 2020. "One model or many? Exchange rates determinants and their predictive capabilities," KAE Working Papers 2020-053, Warsaw School of Economics, Collegium of Economic Analysis.
    39. Fernandez, Viviana & Pastén-Henríquez, Boris & Tapia-Griñen, Pablo & Wagner, Rodrigo, 2023. "Commodity prices under the threat of operational disruptions: Labor strikes at copper mines," Journal of Commodity Markets, Elsevier, vol. 32(C).
    40. Ma, Richie Ruchuan & Xiong, Tao, 2021. "Price explosiveness in nonferrous metal futures markets," Economic Modelling, Elsevier, vol. 94(C), pages 75-90.
    41. Rubaszek, Michał & Karolak, Zuzanna & Kwas, Marek, 2020. "Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 65(C).
    42. Kutan, Ali M. & Shi, Yukun & Wei, Mingzhe & Zhao, Yang, 2018. "Does the introduction of index futures stabilize stock markets? Further evidence from emerging markets," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 183-197.
    43. Pincheira, Pablo & Hardy, Nicolas, 2018. "Forecasting Base Metal Prices with Commodity Currencies," MPRA Paper 83564, University Library of Munich, Germany.
    44. Zian Wang & Xinyi Lu, 2024. "COMEX Copper Futures Volatility Forecasting: Econometric Models and Deep Learning," Papers 2409.08356, arXiv.org.
    45. Zhongxin Ni & Xing Lu & Wenjun Xue, 2021. "Does the belt and road initiative resolve the steel overcapacity in China? Evidence from a dynamic model averaging approach," Empirical Economics, Springer, vol. 61(1), pages 279-307, July.
    46. Khoshalan, Hasel Amini & Shakeri, Jamshid & Najmoddini, Iraj & Asadizadeh, Mostafa, 2021. "Forecasting copper price by application of robust artificial intelligence techniques," Resources Policy, Elsevier, vol. 73(C).
    47. Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, vol. 10(8), pages 1-27, August.

  9. Buncic, Daniel & Martin Melecky, 2013. "Equilibrium Credit: The Reference Point for Macroprudential Supervisors," Economics Working Paper Series 1301, University of St. Gallen, School of Economics and Political Science, revised Feb 2014.

    Cited by:

    1. Han, Rui & Melecky, Martin, 2013. "Financial inclusion for financial stability : access to bank deposits and the growth of deposits in the Global Financial Crisis," Policy Research Working Paper Series 6577, The World Bank.
    2. Mathias Drehmann & James Yetman, 2021. "Which Credit Gap Is Better at Predicting Financial Crises? A Comparison of Univariate Filters," International Journal of Central Banking, International Journal of Central Banking, vol. 17(70), pages 1-31, October.
    3. Daniel Buncic, 2016. "Superforecasting: The Art and Science of Prediction. By Philip Tetlock and Dan Gardner," Risks, MDPI, vol. 4(3), pages 1-5, July.
    4. Mariarosaria Comunale & Markus Eller & Mathias Lahnsteiner, 2020. "Assessing credit gaps in CESEE based on levels justified by fundamentals – a comparison across different estimation approaches," Bank of Lithuania Working Paper Series 74, Bank of Lithuania.
    5. David M. Arseneau & Grace Brang & Matt Darst & Jacob M. M. Faber & David E. Rappoport & Alexandros Vardoulakis, 2022. "A Macroprudential Perspective on the Regulatory Boundaries of U.S. Financial Assets," Finance and Economics Discussion Series 2022-002, Board of Governors of the Federal Reserve System (U.S.).
    6. Ponomarenko, Alexey & Tatarintsev, Stas, 2023. "Incorporating financial development indicators into early warning systems," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    7. Vouldis, Angelos, 2015. "Credit market disequilibrium in Greece (2003-2011) - a Bayesian approach," Working Paper Series 1805, European Central Bank.
    8. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    9. Lang, Jan Hannes & Welz, Peter, 2018. "Semi-structural credit gap estimation," Working Paper Series 2194, European Central Bank.
    10. Melecky, Ales & Melecky, Martin & Sulganova, Monika, 2014. "Úvěry v selhání a makroekonomika: Modelování systémového kreditního rizika v České republice [Non-performing loans and the macroeconomy: Modeling the systemic credit risk in Czech Republic]," MPRA Paper 59917, University Library of Munich, Germany.
    11. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    12. Mathias Drehmann & Kostas Tsatsaronis, 2014. "The credit-to-GDP gap and countercyclical capital buffers: questions and answers," BIS Quarterly Review, Bank for International Settlements, March.
    13. Hosszú, Zsuzsanna & Körmendi, Gyöngyi & Mérő, Bence, 2016. "Egy- és többváltozós szűrők a hitelrés alakulásának meghatározására [Filters with single or multiple variables in measuring the size of the credit gap]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 233-259.
    14. Buncic, Daniel & Moretto, Carlo, 2014. "Forecasting Copper Prices with Dynamic Averaging and Selection Models," Economics Working Paper Series 1430, University of St. Gallen, School of Economics and Political Science.
    15. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    16. Mariarosaria Comunale & Markus Eller & Mathias Lahnsteiner, 2020. "Assessing Credit Gaps in CESEE Based on Levels Justified by Fundamentals – A Comparison Across Different Estimation Approaches (Mariarosaria Comunale, Markus Eller, Mathias Lahnsteiner)," Working Papers 229, Oesterreichische Nationalbank (Austrian Central Bank).
    17. Beck, Thorsten & Feyen, Erik, 2013. "Benchmarking financial systems : introducing the financial possibility frontier," Policy Research Working Paper Series 6615, The World Bank.
    18. Maimbo, Samuel Munzele & Melecky, Martin, 2014. "Financial sector policy in practice : benchmarking financial sector strategies around the world," Policy Research Working Paper Series 6746, The World Bank.
    19. Beck, Thorsten & De Jonghe, Olivier, 2013. "Lending concentration, bank performance and systemic risk : exploring cross-country variation," Policy Research Working Paper Series 6604, The World Bank.
    20. Tihana Skrinjaric & Maja Bukovsak, 2022. "Improving The Calibration Of Countercyclical Capital Buffer: New Indicators Of Credit Gap In Croatia," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, vol. 31(2), pages 541-568, december.
    21. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    22. O'Brien, Martin & Velasco, Sofia, 2020. "Unobserved components models with stochastic volatility for extracting trends and cycles in credit," Research Technical Papers 09/RT/20, Central Bank of Ireland.
    23. Magnus Saß, 2024. "Detecting excessive credit growth: An approach based on structural counterfactuals," Berlin School of Economics Discussion Papers 0046, Berlin School of Economics.
    24. Brown, Martin, 2013. "The transmission of banking crises to households : lessons from the 2008-2011 crises in the ECA region," Policy Research Working Paper Series 6528, The World Bank.

  10. Buncic, Daniel & Martin, Melecky, 2011. "Macroprudential stress testing of credit risk: A practical approach for policy makers," MPRA Paper 33927, University Library of Munich, Germany.

    Cited by:

    1. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
    2. Kelly, Robert & O'Toole, Conor, 2016. "Lending Conditions and Loan Default: What Can We Learn From UK Buy-to-Let Loans?," Research Technical Papers 04/RT/16, Central Bank of Ireland.
    3. Bank for International Settlements, 2020. "Stress testing in Latin America: A comparison of approaches and methodologies," BIS Papers, Bank for International Settlements, number 108.
    4. Akosah, Nana & Loloh, Francis & Lawson, Natalia & Kumah, Claudia, 2018. "Measuring Financial Stability in Ghana: A New Index-Based Approach," MPRA Paper 86634, University Library of Munich, Germany.
    5. Adam Gersl & Petr Jakubik & Tomas Konecny & Jakub Seidler, 2013. "Dynamic Stress Testing: The Framework for Assessing the Resilience of the Banking Sector Used by the Czech National Bank," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(6), pages 505-536, December.
    6. Martin Macháček & Aleš Melecký & Monika Šulganová, 2018. "Macroeconomic Drivers of Non-Performing Loans: A Meta-Regression Analysis," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(3), pages 351-374.
    7. Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.
    8. Buncic, Daniel & Melecky, Martin, 2013. "Equilibrium credit : the reference point for macroprudential supervisors," Policy Research Working Paper Series 6358, The World Bank.
    9. Abildgren, Kim, 2014. "Far out in the tails – The historical distributions of macro-financial risk factors in Denmark," Nationaløkonomisk tidsskrift, Nationaløkonomisk Forening, vol. 2014(1), pages 1-31.
    10. Samuel Fosu & Albert Danso & Henry Agyei-Boapeah & Collins G. Ntim & Emmanuel Adegbite, 2020. "Credit information sharing and loan default in developing countries: the moderating effect of banking market concentration and national governance quality," Review of Quantitative Finance and Accounting, Springer, vol. 55(1), pages 55-103, July.
    11. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    12. Melecky, Ales & Melecky, Martin & Sulganova, Monika, 2014. "Úvěry v selhání a makroekonomika: Modelování systémového kreditního rizika v České republice [Non-performing loans and the macroeconomy: Modeling the systemic credit risk in Czech Republic]," MPRA Paper 59917, University Library of Munich, Germany.
    13. Ventsislav Hristev, 2014. "Bank Stress-Testing Lessons from Central, Eastern and Southeastern European Countries," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 4, pages 92-109, December.
    14. Bakoush, Mohamed & Gerding, Enrico & Mishra, Tapas & Wolfe, Simon, 2022. "An integrated macroprudential stress test of bank liquidity and solvency," Journal of Financial Stability, Elsevier, vol. 60(C).
    15. Kelly, Robert & O’Toole, Conor, 2018. "Mortgage default, lending conditions and macroprudential policy: Loan-level evidence from UK buy-to-lets," Journal of Financial Stability, Elsevier, vol. 36(C), pages 322-335.
    16. Vyshnevskyi, Iegor & Sohn, Wook, 2023. "Nonperforming loans and related lending: Evidence from Ukraine," Emerging Markets Review, Elsevier, vol. 57(C).
    17. Pliszka, Kamil, 2021. "System-wide and banks' internal stress tests: Regulatory requirements and literature review," Discussion Papers 19/2021, Deutsche Bundesbank.
    18. Adam Gersl & Petr Jakubik & Tomas Konecny & Jakub Seidler, 2012. "Dynamic Stress Testing: The Framework for Testing Banking Sector Resilience Used by the Czech National Bank," Working Papers 2012/11, Czech National Bank.
    19. Babasyan, Davit & Gu, Yunfan & Melecky, Martin, 2023. "Late banking transitions: Comparing Uzbekistan to earlier reformers," World Development Perspectives, Elsevier, vol. 30(C).
    20. Asish Saha & Hock-Eam Lim & Goh-Yeok Siew, 2021. "Housing Loan Repayment Behaviour in Malaysia: An Analytical Insight," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 20(2), pages 141-159, September.
    21. Sanatkhani , Mahboobeh & Bazzazan , Fatemeh, 2021. "Stress Testing of Credit Risk in Iran’s Banking System," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(1), pages 93-114, March.
    22. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    23. Petr Jakubík & Tomáš Slacík, 2013. "Measuring Financial (In)Stability in Emerging Europe: A New Index-Based Approach," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 25, pages 102-117.
    24. Busch, Ramona & Koziol, Philipp & Mitrovic, Marc, 2015. "Many a little makes a mickle: Macro portfolio stress test for small and medium-sized German banks," Discussion Papers 23/2015, Deutsche Bundesbank.
    25. Georgios Papadopoulos & Dionysios Chionis & Nikolaos P. Rachaniotis, 2018. "Macro-financial linkages during tranquil and crisis periods: evidence from stressed economies," Risk Management, Palgrave Macmillan, vol. 20(2), pages 142-166, May.
    26. Cecilia Dassatti & Alejandro Pena & Jorge Ponce & Magdalena Tubio, 2014. "Requerimiento de capital contra-cíclico. El caso uruguayo," Documentos de trabajo 2014008, Banco Central del Uruguay.
    27. Ozili, Peterson K & Salman, Asma & Ali, Qaisar, 2020. "The impact of foreign direct investment inflows on nonperforming loans: the case of UAE," MPRA Paper 115825, University Library of Munich, Germany.
    28. International Monetary Fund, 2014. "Malaysia: Financial Sector Assessment Program Financial Sector Performance, Vulnerabilities and Derivatives-Technical Note," IMF Staff Country Reports 2014/098, International Monetary Fund.
    29. Ferrari, Stijn & Van Roy, Patrick & Vespro, Cristina, 2021. "Sensitivity of credit risk stress test results: Modelling issues with an application to Belgium," Journal of Financial Stability, Elsevier, vol. 52(C).
    30. Petr Jakubík & Thomas Reininger, 2013. "Determinants of Nonperforming Loans in Central, Eastern and Southeastern Europe," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 48-66.
    31. Douglas da Rosa München & Herbert Kimura, 2020. "Regulatory Banking Leverage: what do you know?," Working Papers Series 540, Central Bank of Brazil, Research Department.
    32. Egan, Paul & McQuinn, Kieran & O'Toole, Conor, 2022. "A revised financial satellite model for COSMO," Papers WP737, Economic and Social Research Institute (ESRI).
    33. Ghosh, Amit, 2017. "Sector-specific analysis of non-performing loans in the US banking system and their macroeconomic impact," Journal of Economics and Business, Elsevier, vol. 93(C), pages 29-45.
    34. Busch, Ramona & Koziol, Philipp & Mitrovic, Marc, 2018. "Many a little makes a mickle: Stress testing small and medium-sized German banks," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 237-253.
    35. Rasa Kanapickienė & Greta Keliuotytė-Staniulėnienė & Deimantė Vasiliauskaitė & Renatas Špicas & Airidas Neifaltas & Mantas Valukonis, 2023. "Macroeconomic Factors of Consumer Loan Credit Risk in Central and Eastern European Countries," Economies, MDPI, vol. 11(4), pages 1-32, March.
    36. Chuluunbayar, Delgerjargal, 2020. "Macroeconomic determinants of non-performing loans in Mongolia: the influence of currency mismatch and bank size," MPRA Paper 101843, University Library of Munich, Germany.
    37. Svetozar Tanasković & Maja Jandrić, 2015. "Macroeconomic and Institutional Determinants of Non-performing Loans," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 4(1), pages 47-62.
    38. Magdalena Ziolo & Beata Zofia Filipiak & Iwona Bąk & Katarzyna Cheba, 2019. "How to Design More Sustainable Financial Systems: The Roles of Environmental, Social, and Governance Factors in the Decision-Making Process," Sustainability, MDPI, vol. 11(20), pages 1-34, October.

  11. Daniel Buncic, 2009. "Understanding forecast failure of ESTAR models of real exchange rates," EERI Research Paper Series EERI_RP_2009_18, Economics and Econometrics Research Institute (EERI), Brussels.

    Cited by:

    1. Buncic, Daniel & Lentner, Philipp, 2016. "The term structure of interest rates in an estimated New Keynesian policy model," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 126-150.
    2. Peter Martey Addo & Monica Billio & Dominique Guegan, 2014. "The univariate MT-STAR model and a new linearity and unit root test procedure," Post-Print hal-01310518, HAL.
    3. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Understanding Exchange Rates Dynamics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00803447, HAL.
    4. Buncic, Daniel & Melecky, Martin, 2013. "Macroprudential stress testing of credit risk: A practical approach for policy makers," Journal of Financial Stability, Elsevier, vol. 9(3), pages 347-370.
    5. Buncic, Daniel & Melecky, Martin, 2013. "Equilibrium credit : the reference point for macroprudential supervisors," Policy Research Working Paper Series 6358, The World Bank.
    6. Peter Martey Addo & Monica Billio & Dominique Guegan, 2011. "A test for a new modelling: The Univariate MT-STAR Model," Documents de travail du Centre d'Economie de la Sorbonne 11083, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    7. Buncic, Daniel, 2017. "Identification and Estimation issues in Exponential Smooth Transition Autoregressive Models," Working Paper Series 344, Sveriges Riksbank (Central Bank of Sweden).
    8. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    9. Buncic, Daniel & Moretto, Carlo, 2014. "Forecasting Copper Prices with Dynamic Averaging and Selection Models," Economics Working Paper Series 1430, University of St. Gallen, School of Economics and Political Science.
    10. Peter Martey Addo & Monica Billio & Dominique Guegan, 2011. "A New Modelling Test: The Univariate MT-STAR Model," Documents de travail du Centre d'Economie de la Sorbonne 11083r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Aug 2013.
    11. Corina SAMAN, 2015. "Out-Of-Sample Forecasting Performance Of A Robust Neural Exchange Rate Model Of Ron/Usd," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 93-106, March.

  12. Buncic, Daniel & Melecky, Martin, 2007. "An estimated New Keynesian policy model for Australia," MPRA Paper 4138, University Library of Munich, Germany.

    Cited by:

    1. Haider, Adnan & Khan, Safdar Ullah, 2008. "A Small Open Economy DSGE Model for Pakistan," MPRA Paper 12977, University Library of Munich, Germany, revised 17 Jan 2009.
    2. Melecky, Ales & Melecky, Martin, 2008. "From Inflation to Exchange Rate Targeting: Estimating the Stabilization Effects," MPRA Paper 10844, University Library of Munich, Germany.
    3. Martin Melecky & Evgenij Najdov, 2010. "Comparing constraints to economic stabilization in Macedonia and Slovakia: macroestimates with micronarratives," Applied Financial Economics, Taylor & Francis Journals, vol. 20(9), pages 681-699.
    4. Buncic, Daniel & Lentner, Philipp, 2016. "The term structure of interest rates in an estimated New Keynesian policy model," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 126-150.
    5. Eurilton Araújo & Débora Gouveia, 2013. "Calvo-type rules and the forward-looking behavior of inflation targeting central banks," Economics Bulletin, AccessEcon, vol. 33(3), pages 2042-2051.
    6. Martin Melecky, 2008. "A Structural Investigation of Third‐Currency Shocks to Bilateral Exchange Rates," International Finance, Wiley Blackwell, vol. 11(1), pages 19-48, May.
    7. Daniel Rees & Penelope Smith & Jamie Hall, 2015. "A Multi-sector Model of the Australian Economy," RBA Research Discussion Papers rdp2015-07, Reserve Bank of Australia.
    8. Jarkko Jääskelä & Kristoffer Nimark, 2008. "A Medium-scale Open Economy Model of Australia," RBA Research Discussion Papers rdp2008-07, Reserve Bank of Australia.
    9. Syed, Kanwar Abbas, 2009. "Do Money Or Oil And Crop Productivity Shocks Lead To Inflation: The Case Of Pakistan," MPRA Paper 15223, University Library of Munich, Germany.
    10. Zhang, Bo & Dai, Wei, 2020. "Trend inflation and macroeconomic stability in a small open economy," Economic Modelling, Elsevier, vol. 91(C), pages 769-778.
    11. Buncic, Daniel & Melecky, Martin, 2013. "Macroprudential stress testing of credit risk: A practical approach for policy makers," Journal of Financial Stability, Elsevier, vol. 9(3), pages 347-370.
    12. Georgios Georgiadis & Martina Jancokova, 2017. "Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks," Globalization Institute Working Papers 314, Federal Reserve Bank of Dallas.
    13. Melecky, Martin, 2009. "Macroeconomic Management, Financial Sector Development and Crisis Resilience: Some Stylized Facts from Central and Eastern Europe," MPRA Paper 28214, University Library of Munich, Germany, revised 15 Jan 2011.
    14. Buncic, Daniel & Melecky, Martin, 2013. "Equilibrium credit : the reference point for macroprudential supervisors," Policy Research Working Paper Series 6358, The World Bank.
    15. Leu, Shawn Chen-Yu, 2011. "A New Keynesian SVAR model of the Australian economy," Economic Modelling, Elsevier, vol. 28(1-2), pages 157-168, January.
    16. Mardi Dungey & Adrian Pagan, 2008. "Extending an SVAR Model of the Australian Economy," NCER Working Paper Series 21, National Centre for Econometric Research.
    17. Malikane, Christopher & Ojah, Kalu, 2014. "Fisher's Relation and the Term Structure: Implications for IS Curves," MPRA Paper 55553, University Library of Munich, Germany.
    18. Doojav, Gan-Ochir & Gantumur, Munkhbayar, 2020. "Measuring the natural rate of interest in a commodity exporting economy: Evidence from Mongolia," International Economics, Elsevier, vol. 161(C), pages 199-218.
    19. Warwick J McKibbin & Augustus J Panton, 2018. "Twenty-five Years of Inflation Targeting in Australia: Are There Better Alternatives for the Next Twenty-five Years?," RBA Annual Conference Volume (Discontinued), in: John Simon & Maxwell Sutton (ed.),Central Bank Frameworks: Evolution or Revolution?, Reserve Bank of Australia.
    20. Mardi Dungey & Denise Osborn & Mala Raghavan, 2014. "International Transmissions to Australia: The Roles of the USA and Euro Area," The Economic Record, The Economic Society of Australia, vol. 90(291), pages 421-446, December.
    21. Phuong V. Nguyen, 2020. "The Vietnamese business cycle in an estimated small open economy New Keynesian DSGE model," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 48(5), pages 1035-1063, October.
    22. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    23. Van Nguyen, Phuong, 2020. "The Vietnamese business cycle in an estimated small open economy New Keynesian DSGE model," Dynare Working Papers 56, CEPREMAP.
    24. Jarkko P. Jääskelä & Kristoffer P. Nimark, 2011. "A Medium-Scale New Keynesian Open Economy Model of Australia," Working Papers 588, Barcelona School of Economics.
    25. Sheen, Jeffrey & Wang, Ben Zhe, 2016. "Assessing labor market frictions in a small open economy," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 231-251.
    26. Van Nguyen, Phuong, 2020. "Evaluating the forecasting accuracy of the closed- and open economy New Keynesian DSGE models," Dynare Working Papers 59, CEPREMAP.
    27. Harding, Don & Negara, Siwage, 2008. "Estimating baseline real business cycle models of the Australian economy," MPRA Paper 33556, University Library of Munich, Germany.
    28. de Silva, Ashton, 2008. "Forecasting macroeconomic variables using a structural state space model," MPRA Paper 11060, University Library of Munich, Germany.
    29. Gunasinghe, Chandika & Selvanathan, E.A. & Naranpanawa, Athula & Forster, John, 2020. "The impact of fiscal shocks on real GDP and income inequality: What do Australian data say?," Journal of Policy Modeling, Elsevier, vol. 42(2), pages 250-270.
    30. Ara Stepanyan & Ms. Era Dabla-Norris & Ashot Anatolii Mkrtchyan, 2009. "A New Keynesian Model of the Armenian Economy," IMF Working Papers 2009/066, International Monetary Fund.
    31. Kitov, Ivan & Kitov, Oleg, 2011. "The Australian Phillips curve and more," MPRA Paper 28762, University Library of Munich, Germany.
    32. Melecky, Ales & Melecky, Martin, 2010. "From inflation to exchange rate targeting: Estimating the stabilization effects for a small open economy," Economic Systems, Elsevier, vol. 34(4), pages 450-468, December.
    33. Felipe Morandé L. & Mauricio Tejada G., 2009. "Persistent Supply Shocks: A Pain in the Neck for Central Banks?," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 12(3), pages 25-58, December.
    34. Caraiani, Petre, 2008. "An Analysis Of Domestic And External Shocks On Romanian Economy Using A Dsge Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(3), pages 100-114, September.

  13. Brand, Claus & Turunen, Jarkko & Buncic, Daniel, 2006. "The impact of ECB monetary policy decisions and communication on the yield curve," Working Paper Series 657, European Central Bank.

    Cited by:

    1. Marc Anderes & Alexander Rathke & Sina Streicher & Jan-Egbert Sturm, 2019. "The Role of ECB Communication in Guiding Markets," KOF Working papers 19-464, KOF Swiss Economic Institute, ETH Zurich.
    2. Chi Hyun Kim & Lars Other, 2019. "The Short-Run Effect of Monetary Policy Shocks on Credit Risk: An Analysis of the Euro Area," Discussion Papers of DIW Berlin 1781, DIW Berlin, German Institute for Economic Research.
    3. Tillmann, Peter, 2021. "Financial markets and dissent in the ECB’s Governing Council," European Economic Review, Elsevier, vol. 139(C).
    4. Rosa, Carlo & Verga, Giovanni, 2006. "The impact of central bank announcements on asset prices in real time: testing the efficiency of the Euribor futures market," LSE Research Online Documents on Economics 19777, London School of Economics and Political Science, LSE Library.
    5. Buncic, Daniel & Lentner, Philipp, 2016. "The term structure of interest rates in an estimated New Keynesian policy model," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 126-150.
    6. Sui-Jade Ho & Özer Karagedikli, 2021. "Effects of Monetary Policy Communication in Emerging Market Economies: Evidence from Malaysia," Working Papers wp44, South East Asian Central Banks (SEACEN) Research and Training Centre.
    7. Özer Karagedikli & Pierre L. Siklos, 2008. "Explaining Movements in the NZ Dollar - Central Bank Communication and the Surprise Element in Monetary Policy?," Reserve Bank of New Zealand Discussion Paper Series DP2008/02, Reserve Bank of New Zealand.
    8. Afonso, António & Jalles, João Tovar & Kazemi, Mina, 2020. "The effects of macroeconomic, fiscal and monetary policy announcements on sovereign bond spreads," International Review of Law and Economics, Elsevier, vol. 63(C).
    9. Paul Hubert, 2015. "The effect of interest rate and communication shocks on private inflation expectations," Working papers wpaper122, Financialisation, Economy, Society & Sustainable Development (FESSUD) Project.
    10. Ehrmann, Michael & Fratzscher, Marcel, 2007. "Explaining monetary policy in press conferences," Working Paper Series 767, European Central Bank.
    11. Philippe Andrade & Filippo Ferroni, 2018. "Delphic and Odyssean Monetary Policy Shocks: Evidence from the Euro Area," Working Paper Series WP-2018-12, Federal Reserve Bank of Chicago.
    12. Thang, Doan Ngoc & Anh, Pham Thi Hoang & Long, Trinh & Dong, Do Phy & Dat, Luong Van, 2022. "Monetary Stance and Favorableness of Monetary Policy in the Media: The Case of Viet Nam," ADBI Working Papers 1325, Asian Development Bank Institute.
    13. Gergely Hudecz & Elisabetta Vangelista & Robert Blotevogel, 2022. "Asset purchases and sovereign risk premia in the euro area during the pandemic," Working Papers 55, European Stability Mechanism, revised 12 Sep 2022.
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Articles

  1. Daniel Buncic, 2019. "Identification and Estimation Issues in Exponential Smooth Transition Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(3), pages 667-685, June.
    See citations under working paper version above.
  2. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    See citations under working paper version above.
  3. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.

    Cited by:

    1. Daniel Buncic, 2020. "Econometric issues with Laubach and Williams' estimates of the natural rate of interest," Papers 2002.11583, arXiv.org, revised Aug 2020.
    2. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.

  4. Buncic, Daniel & Gisler, Katja I.M., 2017. "The role of jumps and leverage in forecasting volatility in international equity markets," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 1-19.

    Cited by:

    1. Wang, Jiqian & Lu, Xinjie & He, Feng & Ma, Feng, 2020. "Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    2. Li, Xiafei & Liao, Yin & Lu, Xinjie & Ma, Feng, 2022. "An oil futures volatility forecast perspective on the selection of high-frequency jump tests," Energy Economics, Elsevier, vol. 116(C).
    3. Ding, Hui & Huang, Yisu & Wang, Jiqian, 2023. "Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    4. Qiao, Gaoxiu & Teng, Yuxin & Li, Weiping & Liu, Wenwen, 2019. "Improving volatility forecasting based on Chinese volatility index information: Evidence from CSI 300 index and futures markets," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 133-151.
    5. Liu, Guangqiang & Wang, Yan & Chen, Xiaodan & Zhang, Yifeng & Shang, Yue, 2020. "Forecasting volatility of the Chinese stock markets using TVP HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    6. Dimos Kambouroudis & David McMillan & Katerina Tsakou, 2019. "Forecasting Realized Volatility: The role of implied volatility, leverage effect, overnight returns and volatility of realized volatility," Working Papers 2019-03, Swansea University, School of Management.
    7. Anupam Dutta & Kakali Kanjilal & Sajal Ghosh & Donghyun Park & Gazi Salah Uddin, 2023. "Impact of crude oil volatility jumps on sustainable investments: Evidence from India," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1450-1468, October.
    8. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    9. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2021. "Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1618-1639, October.
    10. Zhang, Yue-Jun & Zhang, Han, 2023. "Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?," International Review of Financial Analysis, Elsevier, vol. 85(C).
    11. Jiqian Wang & Feng Ma & Chao Liang & Zhonglu Chen, 2022. "Volatility forecasting revisited using Markov‐switching with time‐varying probability transition," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1387-1400, January.
    12. Feng Ma & Chao Liang & Yuanhui Ma & M.I.M. Wahab, 2020. "Cryptocurrency volatility forecasting: A Markov regime‐switching MIDAS approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1277-1290, December.
    13. Yaojie Zhang & Mengxi He & Yuqi Zhao & Xianfeng Hao, 2023. "Predicting stock realized variance based on an asymmetric robust regression approach," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1022-1047, October.
    14. Chen, Zhonglu & Ye, Yong & Li, Xiafei, 2022. "Forecasting China's crude oil futures volatility: New evidence from the MIDAS-RV model and COVID-19 pandemic," Resources Policy, Elsevier, vol. 75(C).
    15. Xiao, Jihong & Wen, Fenghua & Zhao, Yupei & Wang, Xiong, 2021. "The role of US implied volatility index in forecasting Chinese stock market volatility: Evidence from HAR models," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 311-333.
    16. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    17. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    18. Xiafei Li & Dongxin Li & Xuhui Zhang & Guiwu Wei & Lan Bai & Yu Wei, 2021. "Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1501-1523, December.
    19. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    20. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
    21. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    22. Lu, Xinjie & Ma, Feng & Wang, Jianqiong & Dong, Dayong, 2022. "Singlehanded or joint race? Stock market volatility prediction," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 734-754.
    23. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
    24. Chao Liang & Yan Li & Feng Ma & Yaojie Zhang, 2022. "Forecasting international equity market volatility: A new approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1433-1457, November.
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  5. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    See citations under working paper version above.
  6. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    See citations under working paper version above.
  7. Buncic, Daniel & Lentner, Philipp, 2016. "The term structure of interest rates in an estimated New Keynesian policy model," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 126-150.

    Cited by:

    1. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.

  8. Daniel Buncic & Jon E. Eggins & Robert J. Hill & David Gallagher, 2015. "Measuring fund style, performance and activity: a new style-profiling approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 55(1), pages 29-55, March.

    Cited by:

    1. Michael J. O'Neill & Geoffrey J. Warren, 2019. "Evaluating fund capacity: issues and methods," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 59(S1), pages 773-800, April.
    2. Michael J O’Neill & Zhangxin (Frank) Liu, 2016. "Tail risk hedging for mutual funds using equity market state prices," Australian Journal of Management, Australian School of Business, vol. 41(4), pages 687-698, November.
    3. Michael J. O'Neill & Zhangxin Liu & Tom Smith, 2017. "Fund Volatility Index using equity market state prices," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(3), pages 837-853, September.

  9. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    See citations under working paper version above.
  10. Buncic, Daniel & Melecky, Martin, 2014. "Equilibrium credit: The reference point for macroprudential supervisors," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 135-154.
    See citations under working paper version above.
  11. Buncic, Daniel & Melecky, Martin, 2013. "Macroprudential stress testing of credit risk: A practical approach for policy makers," Journal of Financial Stability, Elsevier, vol. 9(3), pages 347-370.
    See citations under working paper version above.
  12. Daniel Buncic, 2012. "Understanding forecast failure of ESTAR models of real exchange rates," Empirical Economics, Springer, vol. 43(1), pages 399-426, August.
    See citations under working paper version above.
  13. Claus Brand & Daniel Buncic & Jarkko Turunen, 2010. "The Impact of ECB Monetary Policy Decisions and Communication on the Yield Curve," Journal of the European Economic Association, MIT Press, vol. 8(6), pages 1266-1298, December.
    See citations under working paper version above.
  14. Daniel Buncic & Martin Melecky, 2008. "An Estimated New Keynesian Policy Model for Australia," The Economic Record, The Economic Society of Australia, vol. 84(264), pages 1-16, March.
    See citations under working paper version above.
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